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Update app.py
Browse files
app.py
CHANGED
@@ -1,106 +1,397 @@
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import
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import torch
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"3:4": (1140, 1472)
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}
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negative_prompt = " "
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if torch.cuda.is_available():
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torch_dtype = torch.bfloat16
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device = "cuda"
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else:
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torch_dtype = torch.float32
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device = "cpu"
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# Load the pipeline
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pipe = DiffusionPipeline.from_pretrained(model_name, torch_dtype=torch_dtype)
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pipe = pipe.to(device)
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positive_magic = {
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"en": "Ultra HD, 4K, cinematic composition.",
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"zh": "超清,4K,电影级构图"
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}
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def generate_image(prompt):
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"""Generate image from text prompt"""
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# Use the input prompt instead of hardcoded one
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if not prompt.strip():
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prompt = '''A coffee shop entrance features a chalkboard sign reading "Qwen Coffee 😊 $2 per cup," with a neon light beside it displaying "通义千问". Next to it hangs a poster showing a beautiful Chinese woman, and beneath the poster is written "π≈3.1415926-53589793-23846264-33832795-02384197".'''
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width, height = aspect_ratios["16:9"]
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try:
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image = pipe(
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prompt=prompt + " " + positive_magic["en"],
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negative_prompt=negative_prompt,
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width=width,
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height=height,
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num_inference_steps=50,
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true_cfg_scale=4.0,
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generator=torch.Generator(device=device).manual_seed(42) # Use dynamic device
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).images[0]
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# Save the image
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image.save("example.png")
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return image
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return None
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custom_css = """
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.gradio-container {
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}
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text-align: center;
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color: #2c3e50;
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}
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"""
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label="Enter your prompt",
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placeholder="Describe the image you want to generate...",
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lines=3
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)
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generate_btn = gr.Button("Generate Image", variant="primary")
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with gr.Column():
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output_image = gr.Image(label="Generated Image")
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)
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# Launch the interface
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if __name__ == "__main__":
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import os
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import random
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import sys
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from typing import Sequence, Mapping, Any, Union
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import torch
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import gradio as gr
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from PIL import Image
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from huggingface_hub import hf_hub_download
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import base64
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from io import BytesIO
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from openai import OpenAI
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def init_gpt_api():
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return OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
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def base64_to_pil(base64_str):
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image_data = base64.b64decode(base64_str)
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return Image.open(BytesIO(image_data))
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def customize_image(prompt, image):
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if image is None or prompt.strip() == "":
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return None
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prompt = f"Convert this image into a {prompt} drawing"
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client = init_gpt_api()
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# image_base64 = encode_image_from_pil(image)
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result = client.images.edit(
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model="gpt-image-1",
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image=[open(image, 'rb')],
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prompt=prompt,
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)
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if result.data:
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image_base64 = result.data[0].b64_json
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return base64_to_pil(image_base64)
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else:
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return None
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# Create Gradio interface
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custom_css = """
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/* Global styling */
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.gradio-container {
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max-width: 1200px !important;
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margin: 0 auto !important;
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background: linear-gradient(135deg, #667eea 0%, #764ba2 100%) !important;
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min-height: 100vh;
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padding: 20px;
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}
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/* Header styling */
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.main-header {
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background: rgba(255, 255, 255, 0.95);
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backdrop-filter: blur(10px);
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border-radius: 20px;
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padding: 40px;
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margin-bottom: 30px;
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box-shadow: 0 8px 32px rgba(0, 0, 0, 0.1);
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border: 1px solid rgba(255, 255, 255, 0.2);
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text-align: center;
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}
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.main-header h1 {
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background: linear-gradient(45deg, #667eea, #764ba2);
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-webkit-background-clip: text;
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-webkit-text-fill-color: transparent;
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background-clip: text;
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font-size: 3rem !important;
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font-weight: 700 !important;
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margin-bottom: 15px !important;
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text-align: center !important;
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}
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.main-header h3 {
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color: #6b7280 !important;
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text-align: center !important;
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font-weight: 400 !important;
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font-size: 1.3rem !important;
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line-height: 1.6 !important;
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}
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/* Step containers */
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.step-container {
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background: rgba(255, 255, 255, 0.9);
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backdrop-filter: blur(10px);
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border-radius: 16px;
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padding: 30px;
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margin-bottom: 25px;
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box-shadow: 0 4px 20px rgba(0, 0, 0, 0.08);
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border: 1px solid rgba(255, 255, 255, 0.3);
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transition: transform 0.2s ease, box-shadow 0.2s ease;
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}
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.step-container:hover {
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transform: translateY(-2px);
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box-shadow: 0 8px 30px rgba(0, 0, 0, 0.12);
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}
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/* Step headers */
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.step-header {
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display: flex;
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align-items: center;
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margin-bottom: 25px;
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padding-bottom: 20px;
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border-bottom: 3px solid #f3f4f6;
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}
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.step-number {
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background: linear-gradient(45deg, #667eea, #764ba2);
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color: white;
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width: 45px;
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height: 45px;
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border-radius: 50%;
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display: flex;
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align-items: center;
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justify-content: center;
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font-weight: bold;
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font-size: 1.3rem;
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margin-right: 20px;
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box-shadow: 0 4px 15px rgba(102, 126, 234, 0.3);
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}
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.step-title {
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font-size: 1.5rem;
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font-weight: 600;
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color: #374151;
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margin: 0;
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}
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/* Enhanced button styling */
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.primary-button {
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background: linear-gradient(45deg, #667eea, #764ba2) !important;
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border: none !important;
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border-radius: 12px !important;
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padding: 15px 35px !important;
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font-weight: 600 !important;
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font-size: 1.1rem !important;
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color: white !important;
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box-shadow: 0 4px 15px rgba(102, 126, 234, 0.3) !important;
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transition: all 0.3s ease !important;
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margin: 15px 5px !important;
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min-height: 50px !important;
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width: 100% !important;
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}
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.primary-button:hover {
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transform: translateY(-2px) !important;
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box-shadow: 0 6px 25px rgba(102, 126, 234, 0.4) !important;
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}
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.secondary-button {
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background: linear-gradient(45deg, #10b981, #059669) !important;
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border: none !important;
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border-radius: 12px !important;
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padding: 15px 35px !important;
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font-weight: 600 !important;
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font-size: 1.1rem !important;
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color: white !important;
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box-shadow: 0 4px 15px rgba(16, 185, 129, 0.3) !important;
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transition: all 0.3s ease !important;
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margin: 15px 5px !important;
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min-height: 50px !important;
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width: 100% !important;
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}
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.secondary-button:hover {
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transform: translateY(-2px) !important;
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box-shadow: 0 6px 25px rgba(16, 185, 129, 0.4) !important;
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}
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/* Enhanced input styling */
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.gr-textbox input, .gr-dropdown, .gr-slider {
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border: 2px solid #e5e7eb !important;
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border-radius: 10px !important;
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padding: 12px 16px !important;
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font-size: 1rem !important;
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transition: all 0.3s ease !important;
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}
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.gr-textbox input:focus, .gr-dropdown:focus {
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border-color: #667eea !important;
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box-shadow: 0 0 0 3px rgba(102, 126, 234, 0.1) !important;
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outline: none !important;
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}
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/* Upload area enhancement */
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.upload-area {
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border: 3px dashed #667eea;
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border-radius: 15px;
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padding: 10px;
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text-align: center;
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background: linear-gradient(135deg, rgba(102, 126, 234, 0.05), rgba(118, 75, 162, 0.05));
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transition: all 0.3s ease;
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min-height: 150px;
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display: flex;
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align-items: center;
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justify-content: center;
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}
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.upload-area:hover {
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border-color: #764ba2;
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background: linear-gradient(135deg, rgba(102, 126, 234, 0.1), rgba(118, 75, 162, 0.1));
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transform: translateY(-2px);
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}
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/* Image preview styling */
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.image-preview {
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border: 2px solid #e2e8f0;
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border-radius: 12px;
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overflow: hidden;
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box-shadow: 0 4px 15px rgba(0, 0, 0, 0.1);
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background: #f8fafc;
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}
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/* Gallery styling */
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217 |
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.enhanced-gallery {
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border: 2px solid #e2e8f0;
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border-radius: 12px;
|
220 |
+
padding: 15px;
|
221 |
+
background: #f8fafc;
|
222 |
+
min-height: 300px;
|
223 |
+
}
|
224 |
+
|
225 |
+
/* Control groups */
|
226 |
+
.control-group {
|
227 |
+
background: #f8fafc;
|
228 |
+
border: 2px solid #e2e8f0;
|
229 |
+
border-radius: 12px;
|
230 |
+
padding: 20px;
|
231 |
+
margin: 15px 0;
|
232 |
+
}
|
233 |
+
|
234 |
+
.control-group h4 {
|
235 |
+
color: #374151;
|
236 |
+
font-weight: 600;
|
237 |
+
margin-bottom: 15px;
|
238 |
+
text-align: center;
|
239 |
+
}
|
240 |
+
|
241 |
+
/* Info boxes */
|
242 |
+
.info-box {
|
243 |
+
background: linear-gradient(45deg, #dbeafe, #bfdbfe);
|
244 |
+
border: 2px solid #60a5fa;
|
245 |
+
border-radius: 10px;
|
246 |
+
padding: 15px 20px;
|
247 |
+
margin: 15px 0;
|
248 |
+
color: #1e40af;
|
249 |
+
font-weight: 500;
|
250 |
+
}
|
251 |
+
|
252 |
+
.warning-box {
|
253 |
+
background: linear-gradient(45deg, #fef3c7, #fde68a);
|
254 |
+
border: 2px solid #f59e0b;
|
255 |
+
border-radius: 10px;
|
256 |
+
padding: 15px 20px;
|
257 |
+
margin: 15px 0;
|
258 |
+
color: #92400e;
|
259 |
+
font-weight: 500;
|
260 |
+
}
|
261 |
+
|
262 |
+
.success-box {
|
263 |
+
background: linear-gradient(45deg, #d1fae5, #a7f3d0);
|
264 |
+
border: 2px solid #10b981;
|
265 |
+
border-radius: 10px;
|
266 |
+
padding: 15px 20px;
|
267 |
+
margin: 15px 0;
|
268 |
+
color: #065f46;
|
269 |
+
font-weight: 500;
|
270 |
+
}
|
271 |
+
|
272 |
+
/* Section dividers */
|
273 |
+
.section-divider {
|
274 |
+
height: 3px;
|
275 |
+
background: linear-gradient(45deg, #667eea, #764ba2);
|
276 |
+
border-radius: 2px;
|
277 |
+
margin: 30px 0;
|
278 |
+
opacity: 0.7;
|
279 |
+
}
|
280 |
+
|
281 |
+
/* Examples section */
|
282 |
+
.examples-section {
|
283 |
+
background: rgba(255, 255, 255, 0.9);
|
284 |
+
backdrop-filter: blur(10px);
|
285 |
+
border-radius: 16px;
|
286 |
+
padding: 30px;
|
287 |
+
margin-top: 30px;
|
288 |
+
box-shadow: 0 4px 20px rgba(0, 0, 0, 0.08);
|
289 |
+
}
|
290 |
+
/* Responsive design */
|
291 |
+
@media (max-width: 768px) {
|
292 |
+
.gradio-container {
|
293 |
+
padding: 15px;
|
294 |
+
}
|
295 |
|
296 |
+
.main-header {
|
297 |
+
padding: 25px;
|
298 |
+
}
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
299 |
|
300 |
+
.main-header h1 {
|
301 |
+
font-size: 2.5rem !important;
|
302 |
+
}
|
303 |
+
|
304 |
+
.step-container {
|
305 |
+
padding: 20px;
|
306 |
+
}
|
307 |
+
|
308 |
+
.step-number {
|
309 |
+
width: 35px;
|
310 |
+
height: 35px;
|
311 |
+
font-size: 1.1rem;
|
312 |
+
}
|
313 |
|
314 |
+
.step-title {
|
315 |
+
font-size: 1.3rem;
|
316 |
+
}
|
317 |
+
}
|
318 |
+
|
319 |
+
/* Hide default gradio styling conflicts */
|
320 |
+
.gr-box {
|
321 |
+
margin-bottom: 0px !important;
|
322 |
+
border: none !important;
|
323 |
+
}
|
324 |
+
|
325 |
+
.gr-panel {
|
326 |
+
border: none !important;
|
327 |
+
background: transparent !important;
|
328 |
+
}
|
329 |
+
|
330 |
+
.gr-form {
|
331 |
+
background: transparent !important;
|
332 |
+
}
|
333 |
+
"""
|
334 |
+
examples = [
|
335 |
+
["", "mona.png", "receita-tacos.webp", 15, 0.6],
|
336 |
+
["a woman looking at a house catching fire on the background", "disaster_girl.png", "abaporu.jpg", 15, 0.15],
|
337 |
+
["istanbul aerial, dramatic photography", "natasha.png", "istambul.jpg", 15, 0.5],
|
338 |
+
]
|
339 |
+
output_image = gr.Image(label="Generated Image")
|
340 |
+
multi_image = gr.Image(label="Generated Image")
|
341 |
+
# customized_image = gr.Image(label="Customized Image")
|
342 |
+
medium_images = gr.Gallery(label="Images", columns=[2], rows=[2], elem_id="gallery", format="png")
|
343 |
+
|
344 |
+
|
345 |
+
with gr.Blocks(css=custom_css, title="🎨 Artist Ideation - Advanced Style Transfer") as app:
|
346 |
+
# Enhanced Header
|
347 |
+
gr.HTML("""
|
348 |
+
<div class="main-header">
|
349 |
+
<h1>🎨 Artist Ideation</h1>
|
350 |
+
<h3>Advanced Image Medium Transfer </h3>
|
351 |
+
</div>
|
352 |
+
""")
|
353 |
+
|
354 |
+
with gr.Row(elem_classes="step-container"):
|
355 |
+
with gr.Column():
|
356 |
+
gr.HTML("""
|
357 |
+
<div class="step-header">
|
358 |
+
<h2 class="step-title">Artistic Medium Transformation</h2>
|
359 |
+
</div>
|
360 |
+
""")
|
361 |
+
with gr.Row():
|
362 |
+
with gr.Column(scale=1):
|
363 |
+
structure_image = gr.Image(label="Structure Image", type="filepath")
|
364 |
+
custom_medium = gr.Textbox(
|
365 |
+
label="🎨 Artistic Medium",
|
366 |
+
placeholder="Enter your desired medium (e.g., watercolor, charcoal sketch, digital art)...",
|
367 |
+
lines=2,
|
368 |
+
)
|
369 |
+
gr.HTML("""
|
370 |
+
<div class="success-box">
|
371 |
+
💡 <strong>Pro Tips:</strong> Try "watercolor portrait", "pencil sketch", "oil painting masterpiece",
|
372 |
+
or "digital art concept" for best results!
|
373 |
+
</div>
|
374 |
+
""")
|
375 |
+
customize_btn = gr.Button(
|
376 |
+
"🖌️ Transform Medium",
|
377 |
+
variant="primary",
|
378 |
+
elem_classes="secondary-button",
|
379 |
+
size="lg"
|
380 |
+
)
|
381 |
+
|
382 |
+
with gr.Column(scale=1):
|
383 |
+
customized_image = gr.Image(
|
384 |
+
label="🎭 Artistic Transformation",
|
385 |
+
elem_classes="image-preview",
|
386 |
+
height=400
|
387 |
+
)
|
388 |
+
# customized_image.render()
|
389 |
+
|
390 |
+
customize_btn.click(
|
391 |
+
fn=customize_image,
|
392 |
+
inputs=[custom_medium, structure_image],
|
393 |
+
outputs=[customized_image]
|
394 |
)
|
395 |
|
|
|
396 |
if __name__ == "__main__":
|
397 |
+
app.launch(share=True)
|